Immunodominance: a new hypothesis to explain parasite escape and host/parasite equilibrium leading to the chronic phase of Chagas' disease?

Intense immune responses are observed during human or experimental infection with the digenetic protozoan parasite Trypanosoma cruzi. The reasons why such immune responses are unable to completely eliminate the parasites are unknown. The survival of the parasite leads to a parasite-host equilibrium found during the chronic phase of chagasic infection in most individuals. Parasite persistence is recognized as the most likely cause of the chagasic chronic pathologies. Therefore, a key question in Chagas' disease is to understand how this equilibrium is established and maintained for a long period. Understanding the basis for this equilibrium may lead to new approaches to interventions that could help millions of individuals at risk for infection or who are already infected with T. cruzi. Here, we propose that the phenomenon of immunodominance may be significant in terms of regulating the host-parasite equilibrium observed in Chagas' disease. T. cruzi infection restricts the repertoire of specific T cells generating, in some cases, an intense immunodominant phenotype and in others causing a dramatic interference in the response to distinct epitopes. This immune response is sufficiently strong to maintain the host alive during the acute phase carrying them to the chronic phase where transmission usually occurs. At the same time, immunodominance interferes with the development of a higher and broader immune response that could be able to completely eliminate the parasite. Based on this, we discuss how we can interfere with or take advantage of immunodominance in order to provide an immunotherapeutic alternative for chagasic individuals.

THE GENERALIZED MAXIMUM LIKELIHOOD METHOD APPLIED TO HIGH PRESSURE PHASE EQUILIBRIUM

The generalized maximum likelihood method was used to determine binary interaction parameters between carbon dioxide and components of orange essential oil. Vapor-liquid equilibrium was modeled with Peng-Robinson and Soave-Redlich-Kwong equations, using a methodology proposed in 1979 by Asselineau, Bogdanic and Vidal. Experimental vapor-liquid equilibrium data on binary mixtures formed with carbon dioxide and compounds usually found in orange essential oil were used to test the model. These systems were chosen to demonstrate that the maximum likelihood method produces binary interaction parameters for cubic equations of state capable of satisfactorily describing phase equilibrium, even for a binary such as ethanol/CO2. Results corroborate that the Peng-Robinson, as well as the Soave-Redlich-Kwong, equation can be used to describe phase equilibrium for the following systems: components of essential oil of orange/CO2.

HIGH PRESSURE PHASE EQUILIBRIUM: PREDICTION OF ESSENTIAL OIL SOLUBILITY

This work describes a method to predict the solubility of essential oils in supercritical carbon dioxide. The method is based on the formulation proposed in 1979 by Asselineau, Bogdanic and Vidal. The Peng-Robinson and Soave-Redlich-Kwong cubic equations of state were used with the van der Waals mixing rules with two interaction parameters. Method validation was accomplished calculating orange essential oil solubility in pressurized carbon dioxide. The solubility of orange essential oil in carbon dioxide calculated at 308.15 K for pressures of 50 to 70 bar varied from 1.7± 0.1 to 3.6± 0.1 mg/g. For same the range of conditions, experimental solubility varied from 1.7± 0.1 to 3.6± 0.1 mg/g. Predicted values were not very sensitive to initial oil composition.

The industrial equilibrium exchange rate in Brazil: an estimation

This paper presents a methodology for calculating the industrial equilibrium exchange rate, which is defined as the one enabling exporters of state-of-the-art manufactured goods to be competitive abroad. The first section highlights the causes and problems of overvalued exchange rates, particularly the Dutch disease issue, which is neutralized when the exchange rate strikes the industrial equilibrium level. This level is defined by the ratio between the unit labor cost in the country under consideration and in competing countries. Finally, the evolution of this exchange rate in the Brazilian economy is estimated.

The general equilibrium theory as economic metatheory

Many economists show certain nonconformity relative to the excessive mathematical formalization of economics. This stems from dissatisfaction with the old debate about the lack of correspondence between mainstream theoretical models and reality. Although we do not propose to settle this debate here, this article seeks to associate the mismatch of mathematized models with the reality of the adoption of the hypothetical-deductive method as reproduced by general equilibrium. We begin by defining the main benefits of the mathematization of economics. Secondly, we address traditional criticism leveled against it. We then focus on more recent criticism from Gillies (2005) and Bresser-Pereira (2008). Finally, we attempt to associate the reproduction of the hypothetical-deductive method with a metatheoretical process triggered by Debreu's general equilibrium theory. In this respect, we appropriate the ideas of Weintraub (2002), Punzo (1991), and mainly Woo (1986) to support our hypothesis.

Statistical Inference for Computable General Equilibrium Models with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

Political Influence, Economic Interests and Endogenous Tax Structure in a Computable Equilibrium Framework: with Applicatioon to the United States, 1973 and 1983

A full understanding of public affairs requires the ability to distinguish between the policies that voters would like the government to adopt, and the influence that different voters or group of voters actually exert in the democratic process. We consider the properties of a computable equilibrium model of a competitive political economy in which the economic interests of groups of voters and their effective influence on equilibrium policy outcomes can be explicitly distinguished and computed. The model incorporates an amended version of the GEMTAP tax model, and is calibrated to data for the United States for 1973 and 1983. Emphasis is placed on how the aggregation of GEMTAP households into groups within which economic and political behaviour is assumed homogeneous affects the numerical representation of interests and influence for representative members of each group. Experiments with the model suggest that the changes in both interests and influence are important parts of the story behind the evolution of U.S. tax policy in the decade after 1973.

Confidence Regions for Calibrated Parameters in Computable General Equilibrium Models

We consider the problem of accessing the uncertainty of calibrated parameters in computable general equilibrium (CGE) models through the construction of confidence sets (or intervals) for these parameters. We study two different setups under which this can be done.

Methods to Estimate Dynamic Stochastic General Equilibrium Models

This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1 ) Maximum Likelihood, with and without measurement errors and incorporating Bayesian priors, 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) Indirect Inference. Monte Carlo analysis indicates that all procedures deliver reasonably good estimates under the null hypothesis. However, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. GMM and SMM appear to be more robust to misspecification than the alternative procedures. The implications of the stochastic singularity of DSGE models for each estimation method are fully discussed.